1. Field of the Invention
The present invention is related to processing audio data, and more particularly to audio source separation in anechoic environments.
2. Discussion of Prior Art
There is increased interest in using microphone arrays in a variety of audio source separation and consequently speech processing applications. Small arrays of microphones have improved on single microphone systems in speech separation and directional detection of sources for hands free communication and a variety of other speech enhancement and audio source separation applications. Blind or parametric source separation approaches have been applied to distinguish between input from different microphones but with limited success. Challenges such as reverberation, noise, and acoustical echoes still plague many approaches to blind separation of audio signals.
One method for automatically compensating for attenuation due to differences in the calibration of the microphones has been attempted, which implements a deconvolution stage on the order of about a thousand taps. This is computationally expensive and may be difficult to implement in real-time.
A mixing model has been proposed wherein a decorrelation criterion is determined for integer delays, therefore the approach assumes that the distance between the microphones is less than the distance from the sources. However, such assumptions about sources being far-field may not hold well, and thus the model may not be a good approximation of the environment. Another proposed refinement to the mixing model includes higher order tap coefficients. The overall model corresponds to a constrained physical situation.
Another set of related spatial filtering techniques are antenna array processing techniques. Such techniques assume information about the microphone array layout as a given. For example, a delay and attenuation compensation (DAC) separation approach does not necessarily make this assumption, however weaker information such as the distance or a bound on the distance between sensors can help during a parameter estimation phase.
Still other proposed techniques use robust beamforming. Adaptive beamformers assume a known direction of arrival. Beamforming can be applied to source separation to deconvolve source estimates. Various source separation approaches have attempt to combine independent component analysis (ICA) or blind source separation (BSS) and elements of a beamformer to improve the performance of ICA/BSS techniques. However, no known system or method exists for real-time source separation by delay and attenuation compensation.
Therefore, a need exists for a system and method of real-time source separation by delay and attenuation compensation in a time domain.